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The right to refuse diagnostics and treatment planning by artificial intelligence
Medicine, Health Care and Philosophy 23 (1):107-114 (2020)
Abstract
In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physician’s role in the patients’ formation of and acting on personal preferences and values, (2) the bias and opacity problem of AI systems, and (3) rational concerns about the future societal effects of introducing AI systems in the health care sector.Other Versions
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Citations of this work
Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.Sebastian Laacke, Regina Mueller, Georg Schomerus & Sabine Salloch - 2021 - American Journal of Bioethics 21 (7):4-20.
What Are Humans Doing in the Loop? Co-Reasoning and Practical Judgment When Using Machine Learning-Driven Decision Aids.Sabine Salloch & Andreas Eriksen - 2024 - American Journal of Bioethics 24 (9):67-78.
Are clinicians ethically obligated to disclose their use of medical machine learning systems to patients?Joshua Hatherley - forthcoming - Journal of Medical Ethics.
Bias and Epistemic Injustice in Conversational AI.Sebastian Laacke - 2023 - American Journal of Bioethics 23 (5):46-48.
References found in this work
The ethics of algorithms: mapping the debate.Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter & Luciano Floridi - 2016 - Big Data and Society 3 (2):2053951716679679.
How the machine ‘thinks’: Understanding opacity in machine learning algorithms.Jenna Burrell - 2016 - Big Data and Society 3 (1):205395171562251.
Future progress in artificial intelligence: A survey of expert opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent C. Müller, Fundamental Issues of Artificial Intelligence. Cham: Springer. pp. 553-571.
The ethics of big data: current and foreseeable issues in biomedical contexts.Brent Daniel Mittelstadt & Luciano Floridi - 2016 - Science and Engineering Ethics 22 (2):303–341.
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